Genome-Wide Identification and Expression Analysis of YTH Gene Family for Abiotic Stress Regulation in Camellia chekiangoleosa.

N6-methyladenosine (m6A) is essential for RNA metabolism in cells. The YTH domain, conserved in the kingdom of Eukaryotes, acts as an m6A reader that binds m6A-containing RNA. In plants, the YTH domain is involved in plant hormone signaling, stress response regulation, RNA stability, translation, and differentiation. However, little is known about the YTH genes in tea-oil tree, which can produce edible oil with high nutritional value. This study aims to identify and characterize the YTH domains within the tea-oil tree (Camellia chekiangoleosa Hu) genome to predict their potential role in development and stress regulation. In this study, 10 members of the YTH family containing the YTH domain named CchYTH1-10 were identified from C. chekiangoleosa. Through analysis of their physical and chemical properties and prediction of subcellular localization, it is known that most family members are located in the nucleus and may have liquid-liquid phase separation. Analysis of cis-acting elements in the CchYTH promoter region revealed that these genes could be closely related to abiotic stress and hormones. The results of expression profiling show that the CchYTH genes were differentially expressed in different tissues, and their expression levels change under drought stress. Overall, these findings could provide a foundation for future research regarding CchYTHs in C. chekiangoleosa and enrich the world in terms of epigenetic mark m6A in forest trees.

Identification and Expression Patterns of WOX Transcription Factors under Abiotic Stresses in Pinus massoniana.

WUSCHEL-related homeobox (WOX) transcription factors (TFs) play a crucial role in regulating plant development and responding to various abiotic stresses. However, the members and functions of WOX proteins in Pinus massoniana remain unclear. In this study, a total of 11 WOX genes were identified, and bioinformatics methods were used for preliminary identification and analysis. The phylogenetic tree revealed that most PmWOXs were distributed in ancient and WUS clades, with only one member found in the intermediate clade. We selected four highly conserved WOX genes within plants for further expression analysis. These genes exhibited expressions across almost all tissues, while PmWOX2, PmWOX3, and PmWOX4 showed high expression levels in the callus, suggesting their potential involvement in specific functions during callus development. Expression patterns under different abiotic stresses indicated that PmWOXs could participate in resisting multiple stresses in P. massoniana. The identification and preliminary analysis of PmWOXs lay the foundation for further research on analyzing the resistance molecular mechanism of P. massoniana to abiotic stresses.

Student Loss: Towards the Probability Assumption in Inaccurate Supervision.

Noisy labels are often encountered in datasets, but learning with them is challenging. Although natural discrepancies between clean and mislabeled samples in a noisy category exist, most techniques in this field still gather them indiscriminately, which leads to their performances being partially robust. In this paper, we reveal both empirically and theoretically that the learning robustness can be improved by assuming deep features with the same labels follow a student distribution, resulting in a more intuitive method called student loss. By embedding the student distribution and exploiting the sharpness of its curve, our method is naturally data-selective and can offer extra strength to resist mislabeled samples. This ability makes clean samples aggregate tightly in the center, while mislabeled samples scatter, even if they share the same label. Additionally, we employ the metric learning strategy and develop a large-margin student (LT) loss for better capability. It should be noted that our approach is the first work that adopts the prior probability assumption in feature representation to decrease the contributions of mislabeled samples. This strategy can enhance various losses to join the student loss family, even if they have been robust losses. Experiments demonstrate that our approach is more effective in inaccurate supervision. Enhanced LT losses significantly outperform various state-of-the-art methods in most cases. Even huge improvements of over 50% can be obtained under some conditions.

Microbial communities and functions changed in rhizosphere soil of Pinus massoniana provenances with different carbon storage.

Introduction: The average carbon storage of Pinus massoniana is much higher than the average carbon storage of Chinese forests, an important carbon sink tree species in subtropical regions of China. However, there are few studies on the differences in rhizosphere microorganisms of P. massoniana with different carbon storages. Methods: To clarify the relationships between plant carbon storage level, environmental parameters and microbial community structure, we identified three carbon storage levels from different P. massoniana provenances and collected rhizosphere soil samples. We determined chemical properties of soil, extracellular enzyme activity, and microbial community structures at different carbon storage levels and examined how soil factors affect rhizosphere microorganisms under different carbon storage levels. Results: The results revealed that soil organic carbon (SOC), nitrate nitrogen (NO3--N), ammonium nitrogen (NH4+-N) contents all increased with increasing carbon storage levels, while pH decreased accordingly. In contrast, the available phosphorus (AP) content did not change significantly. The soil AP content was within the range of 0.91 ~ 1.04 mg/kg. The microbial community structure of P. massoniana changed with different carbon storage, with Acidobacteria (44.27%), Proteobacteria (32.57%), and Actinobacteria (13.43%) being the dominant bacterial phyla and Basidiomycota (73.36%) and Ascomycota (24.64%) being the dominant fungal phyla across the three carbon storage levels. Soil fungi were more responsive to carbon storage than bacteria in P. massoniana. C/N, NH4+-N, NO3--N, and SOC were the main drivers (p < 0.05) of changes in rhizosphere microbial communities. Discussion: The results revealed that in the rhizosphere there were significant differences in soil carbon cycle and microorganism nutrient preferences at different carbon storages of P. massoniana provenance, which were significantly related to the changes in rhizosphere microbial community structure. Jiangxi Anyuan (AY) provenance is more suitable for the construction of high carbon storage plantation.

Transcriptome-Wide Identification of TCP Transcription Factor Family Members in Pinus massoniana and Their Expression in Regulation of Development and in Response to Stress.

Pinus massoniana is an important coniferous tree species for barren mountain afforestation with enormous ecological and economic significance. It has strong adaptability to the environment. TEOSINTE BRANCHED 1/CYCLOIDEA/PCF (TCP) transcription factors (TFs) play crucial roles in plant stress response, hormone signal transduction, and development processes. At present, TCP TFs have been widely studied in multiple plant species, but research in P. massoniana has not been carried out. In this study, 13 PmTCP TFs were identified from the transcriptomes of P. massoniana. The phylogenetic results revealed that these PmTCP members were divided into two categories: Class I and Class II. Each PmTCP TF contained a conserved TCP domain, and the conserved motif types and numbers were similar in the same subgroup. According to the transcriptional profiling analysis under drought stress conditions, it was found that seven PmTCP genes responded to drought treatment to varying degrees. The qRT-PCR results showed that the majority of PmTCP genes were significantly expressed in the needles and may play a role in the developmental stage. Meanwhile, the PmTCPs could respond to several stresses and hormone treatments at different levels, which may be important for stress resistance. In addition, PmTCP7 and PmTCP12 were nuclear localization proteins, and PmTCP7 was a transcriptional suppressor. These results will help to explore the regulatory factors related to the growth and development of P. massoniana, enhance its stress resistance, and lay the foundation for further exploration of the physiological effects on PmTCPs.

Genome-Wide Identification and Characterization of the YTH Domain-Containing RNA-Binding Protein Family in Liriodendron chinense.

N6-methyladenosine (m6A) is becoming one of the most important RNA modifications in plant growth and development, including defense, cell differentiation, and secondary metabolism. YT521-B homology (YTH) domain-containing RNA-binding proteins, identified as m6A readers in epitranscriptomics, could affect the fate of m6A-containing RNA by recognizing and binding the m6A site. Therefore, the identification and study of the YTH gene family in Liriodendron chinense (L. chinense) can provide a molecular basis for the study of the role of m6A in L. chinense, but studies on the YTH gene in L. chinense have not been reported. We identified nine putative YTH gene models in the L. chinense genome, which can be divided into DF subgroups and DC subgroups. Domain sequence analysis showed that the LcYTH protein had high sequence conservation. A LcYTH aromatic cage bag is composed of tryptophan and tryptophan (WWW). PrLDs were found in the protein results of YTH, suggesting that these genes may be involved in the process of liquid-liquid phase separation. LcYTH genes have different tissue expression patterns, but the expression of LcYTHDF2 is absolutely dominant in all tissues. In addition, the expression of the LcYTH genes is changed in response to ABA and MeJA. In this study, We identified and analyzed the expression pattern of LcYTH genes. Our results laid a foundation for further study of the function of the LcYTH gene and further genetic and functional analyses of m6A RNA modification in forest trees.

The Transcriptomic Analysis of the Response of Pinus massoniana to Drought Stress and a Functional Study on the ERF1 Transcription Factor.

Pinus massoniana is a major fast-growing timber tree species planted in arid areas of south China, which has a certain drought-resistant ability. However, severe drought and long-term water shortage limit its normal growth and development. Therefore, in this study, physiological indices, and the transcriptome sequencing and cloning of AP2/ERF transcription factor of P. massonsiana were determined to clarify its molecular mechanism of drought stress. The results showed that stomatal conductance (Gs) content was significantly decreased, and superoxide dismutase (SOD) activity, and malondialdehyde (MDA) and abscisic acid (ABA) content were significantly increased under drought stress. Transcriptomic analysis revealed that compared to the control, 9, 3550, and 4142 unigenes with differential expression were identified by comparing plants subjected to light, moderate or severe drought. AP2/ERF with high expression was screened out for cloning. To investigate the biological functions of ERF1, it was over-expressed in wild-type Populus davdianaand × P. bolleana via the leaf disc method. Under drought stress, compared to wild-type plants, ERF1 over-expressing poplar lines (OE) maintained a higher photosynthetic rate and growth, while the transpiration rate and stomatal conductance significantly decreased and water use efficiency was improved, indicating that drought tolerance was enhanced. This study provides an insight into the molecular mechanism of drought stress adaptation in P. massoniana.

Transcriptome-Wide Identification of CCCH-Type Zinc Finger Proteins Family in Pinus massoniana and RR-TZF Proteins in Stress Response.

CCCH-type zinc finger proteins play an important role in multiple biotic and abiotic stresses. More and more reports about CCCH functions in plant development and stress responses have appeared over the past few years, focusing especially on tandem CCCH zinc finger proteins (TZFs). However, this has not been reported in Pinaceae. In this study, we identified 46 CCCH proteins, including 6 plant TZF members in Pinus massoniana, and performed bioinformatic analysis. According to RT-PCR analysis, we revealed the expression patterns of five RR-TZF genes under different abiotic stresses and hormone treatments. Meanwhile, tissue-specific expression analysis suggested that all genes were mainly expressed in needles. Additionally, RR-TZF genes showed transcriptional activation activity in yeast. The results in this study will be beneficial in improving the stress resistance of P. massoniana and facilitating further studies on the biological and molecular functions of CCCH zinc finger proteins.

Adaptive Graph Guided Disambiguation for Partial Label Learning.

In partial label learning, a multi-class classifier is learned from the ambiguous supervision where each training example is associated with a set of candidate labels among which only one is valid. An intuitive way to deal with this problem is label disambiguation, i.e., differentiating the labeling confidences of different candidate labels so as to try to recover ground-truth labeling information. Recently, feature-aware label disambiguation has been proposed which utilizes the graph structure of feature space to generate labeling confidences over candidate labels. Nevertheless, the existence of noises and outliers in training data makes the graph structure derived from original feature space less reliable. In this paper, a novel partial label learning approach based on adaptive graph guided disambiguation is proposed, which is shown to be more effective in revealing the intrinsic manifold structure among training examples. Other than the sequential disambiguation-then-induction learning strategy, the proposed approach jointly performs adaptive graph construction, candidate label disambiguation and predictive model induction with alternating optimization. Furthermore, we consider the particular human-in-the-loop framework in which a learner is allowed to actively query some ambiguously labeled examples for manual disambiguation. Extensive experiments clearly validate the effectiveness of adaptive graph guided disambiguation for learning from partial label examples.